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A fuzzy geographical routing approach to support real-time multimedia transmission for vehicular ad hoc networks

  • Imane Zaimi
  • Abdelali Boushaba
  • Zineb Squalli Houssaini
  • Mohammed Oumsis
Article
  • 64 Downloads

Abstract

Vehicular ad hoc networks known by their greatly active topology have given rise to new challenges related to routing protocols, issues of less concern in infrastructure-based networks or even in mobile ad hoc networks. Indeed, the high revocability of network topology makes the satisfaction of driver’s requirements very arduous, especially with multimedia applications that need strict quality of service (QoS) support. The main purpose of this paper is to promote real time video traffic by maximizing user gratification while keeping a good QoS. Thus, based on the well-known greedy perimeter stateless routing (GPSR) protocol, we propose a new approach called fuzzy geographical routing (FzGR) that incorporates two fuzzy logic usages. The first takes into consideration three input parameters of QoS: the delay, the size of buffer and the throughput, while it outputs a single relevant metric to prioritize the next-hop with lower concern. The other fuzzy system aims at preserving the concept of basic GPSR by considering the distance measure between each next-hop and the final destination. The proposal has been evaluated and compared to the GPSR using a rigorous metrics analysis regarding QoS and quality of experience. Our extensive experimental results using several simulators (e.g., NS-2, VanetMobiSim and Evalvid), show that FzGR has the ability to increase the performance of the network.

Keywords

VANETs IEEE 802.11p GPSR Multimedia transmission Fuzzy system QoS QoE 

References

  1. 1.
    Yang, F., Wang, S., Li, J., Liu, Z., & Sun, Q. (2014). An overview of internet of vehicles. China Communications, 11(10), 1–15.CrossRefGoogle Scholar
  2. 2.
    Rehman, O., Ould-Khaoua, M., & Bourdoucen, H. (2016). An adaptive relay nodes selection scheme for multi-hop broadcast in VANETs. Computer Communications, 87, 76–90.CrossRefGoogle Scholar
  3. 3.
    Marfia, G., Roccetti, M., Amoroso, A., & Pau, G. (2013). Safe driving in LA: Report from the greatest intervehicular accident detection test ever. IEEE Transactions on Vehicular Technology, 62(2), 522–535.CrossRefGoogle Scholar
  4. 4.
    Liu, J., Wan, J., Wang, Q., Deng, P., Zhou, K., & Qiao, Y. (2016). A survey on position-based routing for vehicular ad hoc networks. Telecommunication Systems, 62(1), 15–30.CrossRefGoogle Scholar
  5. 5.
    Zarei, M., Rahmani, A. M., & Samimi, H. (2017). Connectivity analysis for dynamic movement of vehicular ad hoc networks. Wireless Networks, 23(3), 843–858.CrossRefGoogle Scholar
  6. 6.
    Jiang, D., & Delgrossi, L. (2008). IEEE 802.11 p: Towards an international standard for wireless access in vehicular environments. In Vehicular technology conference, 2008. VTC spring 2008. IEEE (pp. 2036–2040). IEEE.Google Scholar
  7. 7.
    Sharef, B. T., Alsaqour, R. A., & Ismail, M. (2013). Comparative study of variant position-based VANET routing protocols. Procedia Technology, 11, 532–539.CrossRefGoogle Scholar
  8. 8.
    Jabbarpour, M. R., Marefat, A., Jalooli, A., Noor, R. M., Khokhar, R. H., & Lloret, J. (2015). Performance analysis of V2V dynamic anchor position-based routing protocols. Wireless Networks, 21(3), 911–929.CrossRefGoogle Scholar
  9. 9.
    Zaimi, I., Houssaini, Z.S., Boushaba, A., & Oumsis, M. (2016). An improved GPSR protocol to enhance the video quality transmission over vehicular ad hoc networks. In 2016 international conference on wireless networks and mobile communications (WINCOM) (pp. 146–153). IEEE.Google Scholar
  10. 10.
    Wischhof, L., Ebner, A., & Rohling, H. (2005). Information dissemination in self-organizing intervehicle networks. IEEE Transactions on Intelligent Transportation Systems, 6(1), 90–101.CrossRefGoogle Scholar
  11. 11.
    Zadeh, L.A. (1988). Fuzzy logic. Computer, 21(4), 83–93.CrossRefGoogle Scholar
  12. 12.
    Boushaba, A., Benabbou, A., Benabbou, R., Zahi, A., & Oumsis, M. (2014). Intelligent multipath optimized link state routing protocol for QoS and QoE enhancement of video transmission in MANETs. In Networked systems. Lecture Notes in Computer Science (Vol. 8593, pp. 230–245). Cham: Springer.Google Scholar
  13. 13.
    Kumuthini, C., & Krishnakumari, P. (2016). Evolving intuitionistic fuzzy priority classifier with bio-inspiration based scheduling scheme for WiMAX in vehicular ad-hoc networks. Wireless Networks, 22(2), 403–415.CrossRefGoogle Scholar
  14. 14.
    Boushaba, A., Benabbou, A., Benabbou, R., Zahi, A., & Oumsis, M. (2016). An intelligent multipath optimized link state routing protocol for QoS and QoE enhancement of video transmission in MANETs. Computing, 98(8), 803–825.MathSciNetCrossRefGoogle Scholar
  15. 15.
    Jiau, M. K., Huang, S. C., Hwang, J. N., & Vasilakos, A. V. (2015). Multimedia services in cloud-based vehicular networks. IEEE Intelligent Transportation Systems Magazine, 7(3), 62–79.CrossRefGoogle Scholar
  16. 16.
    Naeimipoor, F., Rezende, C., & Boukerche, A. (2012). Performance evaluation of video dissemination protocols over vehicular networks. In 2012 IEEE 37th conference on local computer networks workshops (LCN Workshops) (pp. 694–701). IEEE.Google Scholar
  17. 17.
    Xie, F., Hua, K. A., Wang, W., & Ho, Y. H. (2007). Performance study of live video streaming over highway vehicular ad hoc networks. In 2007 IEEE 66th vehicular technology conference (pp. 2121–2125). IEEE.Google Scholar
  18. 18.
    Zaimi, I., Houssaini, Z. S., Boushaba, A., & Oumsis, M. (2016). A new improved GPSR (GPSR-kP) routing protocol for multimedia communication over vehicular ad hoc network. In Proceedings of the international conference on big data and advanced wireless technologies (p. 14). ACM.Google Scholar
  19. 19.
    Kwon, S., & Shroff, N. B. (2006). Geographic routing in the presence of location errors. Computer Networks, 50(15), 2902–2917.CrossRefzbMATHGoogle Scholar
  20. 20.
    Shah, R. C., Wolisz, A., & Rabaey, J. M. (2005). On the performance of geographical routing in the presence of localization errors [ad hoc network applications]. In 2005 IEEE international conference on communications, 2005. ICC 2005 (Vol. 5, pp. 2979–2985). IEEE.Google Scholar
  21. 21.
    Kaur, S., & Kaur, K. (2016). An new improved GPSR (I-GPSR) routing protocol for VANET. Imperial Journal of Interdisciplinary Research, 2(7), 1192–1196.Google Scholar
  22. 22.
    Bouras, C., Kapoulas, V., & Tsanai, E. (2015). A GPSR enhancement mechanism for routing in VANETs. In Wired/wireless internet communications. Lecture Notes in Computer Science (Vol. 9071, pp. 94–107). Berlin: Springer.Google Scholar
  23. 23.
    Zhang, X. M., Chen, K. H., Cao, X. L., & Sung, D. K. (2016). A street-centric routing protocol based on microtopology in vehicular ad hoc networks. IEEE Transactions on Vehicular Technology, 65(7), 5680–5694.CrossRefGoogle Scholar
  24. 24.
    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 Proceedings of the 3rd international workshop on vehicular ad hoc networks (pp. 88–89). ACM.Google Scholar
  25. 25.
    Zhang, X., Cao, X., Yan, L., & Sung, D. K. (2016). A street-centric opportunistic routing protocol based on link correlation for urban vanets. IEEE Transactions on Mobile Computing, 15(7), 1586–1599.CrossRefGoogle Scholar
  26. 26.
    Alsaqour, R., Abdelhaq, M., Saeed, R., Uddin, M., Alsukour, O., Al-Hubaishi, M., et al. (2015). Dynamic packet beaconing for GPSR mobile ad hoc position-based routing protocol using fuzzy logic. Journal of Network and Computer Applications, 47, 32–46.CrossRefGoogle Scholar
  27. 27.
    Khokhar, R. H., Noor, R. M., Ghafoor, K. Z., Ke, C. H., & Ngadi, M. A. (2011). Fuzzy-assisted social-based routing for urban vehicular environments. EURASIP Journal on Wireless Communications and Networking, 2011(1), 178.CrossRefGoogle Scholar
  28. 28.
    Boukerche, A., Câmara, D., Loureiro, A. A., & Figueiredo, C. M. (2009). Algorithms for mobile ad hoc networks. Algorithms and protocols for wireless and mobile ad hoc networks, Chapter 1 (pp. 1–20). Wiley.Google Scholar
  29. 29.
    Ramanathan, R., & Rosales-Hain, R. (2000). Topology control of multihop wireless networks using transmit power adjustment. In INFOCOM 2000. Nineteenth annual joint conference of the IEEE computer and communications societies. Proceedings. IEEE (Vol. 2, pp. 404–413). IEEE.Google Scholar
  30. 30.
    Takagi, H., & Kleinrock, L. (1984). Optimal transmission ranges for randomly distributed packet radio terminals. IEEE Transactions on Communications, 32(3), 246–257.CrossRefGoogle Scholar
  31. 31.
    Ghazani, S. H. H. N. (2013). Algorithms for mobile ad hoc networks. In 2013 7th international conference on application of information and communication technologies (AICT) (pp. 1–4). IEEE.Google Scholar
  32. 32.
    Hou, T. C., & Li, V. (1986). Transmission range control in multihop packet radio networks. IEEE Transactions on Communications, 34(1), 38–44.CrossRefGoogle Scholar
  33. 33.
    Finn, G. G. (1987). Routing and addressing problems in large metropolitan-scale internetworks. Technical report., DTIC Document.Google Scholar
  34. 34.
    Karp, B., & Kung, H. T. (2000). GPSR: Greedy perimeter stateless routing for wireless networks. In Proceedings of the 6th annual international conference on Mobile computing and networking (pp. 243–254). ACM.Google Scholar
  35. 35.
    Zaimi, I., Houssaini, Z. S., Boushaba, A., Oumsis, M., & Aboutajdine, D. (2018). An evaluation of routing protocols for vehicular ad-hoc network considering the video stream. Wireless Personal Communications, 98(1), 945–981.CrossRefGoogle Scholar
  36. 36.
    Boushaba, A., Benabbou, A., Benabbou, R., Zahi, A., & Oumsis, M. (2015). Multi-point relay selection strategies to reduce topology control traffic for OLSR protocol in MANETs. Journal of Network and Computer Applications, 53, 91–102.CrossRefGoogle Scholar
  37. 37.
    Zhao, J., & Bose, B. K. (2002) Evaluation of membership functions for fuzzy logic controlled induction motor drive. In IECON 02. IEEE 2002 28th annual conference of the industrial electronics society (Vol. 1, pp. 229–234). IEEE.Google Scholar
  38. 38.
    Sugeno, M. (1985). An introductory survey of fuzzy control. Information Sciences, 36(1), 59–83.MathSciNetCrossRefzbMATHGoogle Scholar
  39. 39.
    Zadeh, L. A. (1965). Information and control. Fuzzy Sets, 8(3), 338–353.Google Scholar
  40. 40.
    Cirstea, M., Dinu, A., McCormick, M., & Khor, J. G. (2002). Neural and fuzzy logic control of drives and power systems. Oxford: Newnes.Google Scholar
  41. 41.
    Horikawa, S. I., Furuhashi, T., Okuma, S., & Uchikawa, Y. (1990). Composition methods of fuzzy neural networks. In 16th annual conference of IEEE industrial electronics society, 1990. IECON’90 (pp. 1253–1258). IEEE .Google Scholar
  42. 42.
    Mamdani, E. H. (1974). Application of fuzzy algorithms for control of simple dynamic plant. Proceedings of the Institution of Electrical Engineers, 121(12), 1585–1588.CrossRefGoogle Scholar
  43. 43.
    Camastra, F., Ciaramella, A., Giovannelli, V., Lener, M., Rastelli, V., Staiano, A., et al. (2015). A fuzzy decision system for genetically modified plant environmental risk assessment using Mamdani inference. Expert Systems with Applications, 42(3), 1710–1716.CrossRefzbMATHGoogle Scholar
  44. 44.
    Mohammad, R., Mostafa, A., Abbas, M., & Farouq, H. M. (2015). Prediction of representative deformation modulus of longwall panel roof rock strata using Mamdani fuzzy system. International Journal of Mining Science and Technology, 25(1), 23–30.CrossRefGoogle Scholar
  45. 45.
    Boukerche, A. (2008). Algorithms and protocols for wireless, mobile ad hoc networks (Vol. 77). New York: Wiley.CrossRefzbMATHGoogle Scholar
  46. 46.
    Artimy, M. M., Robertson, W., & Phillips, W. J. (2009). Vehicular ad hoc networks: An emerging technology toward safe and efficient transportation. Algorithms and Protocols for Wireless and Mobile Ad Hoc Networks, Wiley, Chapter 14 (pp. 433–457). Wiley.Google Scholar
  47. 47.
    Chen, Z. D., Kung, H., & Vlah, D. (2001). Ad hoc relay wireless networks over moving vehicles on highways. In Proceedings of the 2nd ACM international symposium on Mobile ad hoc networking and computing (pp. 247–250). ACM .Google Scholar
  48. 48.
    Füßler, H., Mauve, M., Hartenstein, H., Käsemann, M., & Vollmer, D. (2004). A comparison of routing strategies for vehicular ad hoc networks. Technical reports (Vol. 2).Google Scholar
  49. 49.
    Rahman, M. H., Morshed, M. M., & Rahman, M. U. (2014). Realistic vehicular mobility impact of FTM, IDM, IDM-IM and IDM-LC on VANETs. International Journal of Computer Applications, 90(11), 1712–1719.Google Scholar
  50. 50.
    De Felice, M., Cerqueira, E., Melo, A., Gerla, M., Cuomo, F., & Baiocchi, A. (2015). A distributed beaconless routing protocol for real-time video dissemination in multimedia VANETs. Computer Communications, 58, 40–52.CrossRefGoogle Scholar
  51. 51.
    Park, J. S., Lee, U., & Gerla, M. (2010). Vehicular communications: Emergency video streams and network coding. Journal of Internet Services and Applications, 1(1), 57–68.CrossRefGoogle Scholar
  52. 52.
    Ziviani, A., Wolfinger, B. E., De Rezende, J. F., Duarte, O. C. M., & Fdida, S. (2005). Joint adoption of QoS schemes for MPEG streams. Multimedia Tools and Applications, 26(1), 59–80.CrossRefGoogle Scholar
  53. 53.
    Graphics, M. (2009). Media lab. Msu video quality measurement tool. http://compression.ru/video/quality_measure/video_measurement_tool_en.html. Accessed Jan 2009.
  54. 54.
    Chikkerur, S., Sundaram, V., Reisslein, M., & Karam, L. J. (2011). Objective video quality assessment methods: A classification, review, and performance comparison. IEEE Transactions on Broadcasting, 57(2), 165–182.CrossRefGoogle Scholar
  55. 55.
    Cacheda, R., García, D., Cuevas, A., Castaño, F., Sánchez, J., Koltsidas, G., Mancuso, V., Novella, J., Oh, S., & Pantò, A. (2007). QoS requirements for multimedia services. Resource management in satellite networks (pp. 67–94). Boston, MA: Springer.Google Scholar
  56. 56.
    Khan, I., & Qayyum, A. (2009). Performance evaluation of AODV and OLSR in highly fading vehicular ad hoc network environments. In IEEE 13th international multitopic conference, 2009. INMIC 2009 (pp. 1–5). IEEE.Google Scholar
  57. 57.
    Lee, K. C., Härri, J., Lee, U., & Gerla, M. (2007). Enhanced perimeter routing for geographic forwarding protocols in urban vehicular scenarios. In Globecom workshops, 2007 IEEE (pp. 1–10). IEEE.Google Scholar
  58. 58.
    Barba, C. T., Aguiar, L. U., & Igartua, M. A. (2013). Design and evaluation of GBSR-B, an improvement of GPSR for VANETs. IEEE Latin America Transactions, 11(4), 1083–1089.CrossRefGoogle Scholar
  59. 59.
    Tripp-Barba, C., Urquiza-Aguiar, L., Igartua, M. A., Rebollo-Monedero, D., de la Cruz Llopis, L. J., Mezher, A. M., et al. (2014). A multimetric, map-aware routing protocol for VANETs in urban areas. Sensors, 14(2), 2199–2224.CrossRefGoogle Scholar
  60. 60.
    Chen, Y., Li, C., Han, X., Gao, M., & Zhu, L. (2014). A reliable beaconless routing protocol for VANETs. In 2014 IEEE international conference on computer and information technology (CIT) (pp. 94–99). IEEE.Google Scholar
  61. 61.
    Li, G., Ma, M., Liu, C., & Shu, Y. (2015). Adaptive fuzzy multiple attribute decision routing in VANETs. International Journal of Communication Systems, 30(4).Google Scholar
  62. 62.
    Bouras, C., Kapoulas, V., Stathopoulos, N., & Gkamas, A. (2016). Mechanisms for enhancing the performance of routing protocols in VANETs. In Proceedings of the 13th ACM symposium on performance evaluation of wireless ad hoc, sensor, and ubiquitous networks (pp. 11–18). ACM.Google Scholar
  63. 63.
    Gupta, K. P. (2016). A review on multipath vehicular ad hoc routing protocol (VANET) routing protocol. International Journal of Science, Engineering and Technology Research (IJSETR), 5(5), 1712–1719.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Imane Zaimi
    • 1
  • Abdelali Boushaba
    • 2
  • Zineb Squalli Houssaini
    • 3
  • Mohammed Oumsis
    • 1
    • 4
  1. 1.LRIT, Associated Unit to CNRST (URAC 29), Faculty of SciencesMohammed-V UniversityRabatMorocco
  2. 2.Intelligent Systems and Applications Laboratory (LSIA), Faculty of Sciences and TechnologySidi Mohamed Ben Abdelah UniversityFezMorocco
  3. 3.IT laboratory and Modelling (LIM), Dhar El Mahraz Faculty of Sciences (FSDM)Sidi Mohammed Ben Abdellah University (USMBA)FezMorocco
  4. 4.Superior school of TechnologyMohammed-V UniversityRabatMorocco

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