Skip to main content
SpringerLink
Log in

Routing Protocol Based Quality of Service and Links Stability (RPQLS) for Future Internet of Vehicles

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Internet of Vehicles (IoV) is a significant part of the Internet of Things. However, vehicles in IoV network are characterized by their high mobility, which makes it challenging to maintain stable communication stability and high quality of service. A clustering protocol provides an efficient solution to ensure high quality of service for vehicles and increase the network’s communication lifetime by grouping vehicles into clusters to reduce network overhead and ensure load balancing between resources. However, existing clustering models have several issues that impact network performance, such as choosing ineffective metrics to select routes between cluster heads and between cluster members. Additionally, most clustering communication techniques fail to adapt to the unique characteristics of IoVs. Therefore, the effectiveness of clustering communication algorithms has a significant impact on the communication’s lifetime. In this paper, we propose a Routing Protocol based Quality of Service and Links Stability (RPQLS) that aims to ensure route stability according to two levels. In the first one, the best routes are discovered by using metrics such as signal strength, bandwidth, delay and node velocity. In the second level, an approach for estimating links lifetime has been used. The latter is based on speed and direction parameters in order to find the most durable route. To this end, the Fuzzy Logic method has been used to reach our objective. The performance evaluation of RPQLS has been carried out through the NS-3 simulator and compared with GICA, QoS Cluster and weight-based protocols. RPQLS improves the PDR by 20%, delay by 41% and network overhead by 41%.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22

Similar content being viewed by others

Data Availability

All data is provided in full in the results section of this paper.

Code Availability

The code source used in this study is available from the corresponding author upon reasonable request.

References

  1. Kaiwartya, O., Abdullah, A. H., Cao, Y., Altameem, A., Prasad, M., Lin, C., & Liu, X. (2016). Internet of vehicles: Motivation, layered architecture, network model, challenges, and future aspects. IEEE Access, 4, 5356–5373.

    Article  Google Scholar 

  2. Gerla, M., Lee, E., Pau, G., & Lee, U. (2014). Internet of vehicles: From Intelligent grid to autonomous cars and vehicular clouds. In IEEE world forum on Internet of Things (WF-IoT) Seoul.

  3. Khorov, E., Lyakhov, A., Krotov, A., & Guschin, A. (2014). A survey on IEEE 802.11 ah: An enabling networking technology for smart cities. Computer Communications, 58(1), 5369.

    Google Scholar 

  4. Cooper, C., Franklin, D. R., Ros, M., & Abolhasan, M. (2016). A comparative survey of VANET clustering techniques. IEEE Communications Surveys & Tutorials, 19, 657.

    Article  Google Scholar 

  5. Ren, M., Khoukhi, L., Labiod, H., Zhang, J., & Vèque, V. (2017). A mobility-based scheme for dynamic clustering in vehicular ad-hoc networks (VANETs). Vehicular Communications, 9, 233–241.

    Article  Google Scholar 

  6. Aadil, F., Ahsan, W., Rehman, Z., Shah, P., Rho, S., & Mehmood, I. (2018). Clustering algorithm for internet of vehicles (IoV) based on dragonfly optimizer (CAVDO). The Journal of Supercomputing, 74, 4552–4567.

    Article  Google Scholar 

  7. Fahad Khan, M., Aadil, F., Maqsood, M., Bukhari, S. H. R., Hussain, M., & Nam, Y. (2019). Moth flame clustering algorithm for Internet of Vehicle (MFCA-IoV). IEEE Access, 7, 11613–11629.

    Article  Google Scholar 

  8. Gasmi, R., & Aliouat, M. (2020). A weight based clustering algorithm for Internet of Vehicles. Automatic Control and Computer Sciences, 54, 493–500.

    Article  Google Scholar 

  9. Bellaouar, S., Guerroumi, M., & Moussaoui, S. (2019). QoS based clustering for vehicular networks in smart cities. In Dependability in sensor, cloud, and big data systems and applications, 5th international conference, DependSys, Guangzhou, China, November 12–15.

  10. Song, T., Xia, W., Song, T., & Shen, L. (2010). A cluster-based directional routing protocol in VANET. In IEEE 12th international conference on communication technology (pp. 1172–1175). China.

  11. Gasmi, R., Aliouat, M., & Seba, H. (2020). Geographical information based clustering algorithm for Internet of Vehicles. In Machine learning for networking: third international conference, MLN 2020. Paris, France, November 24–26.

  12. Sharif, A., Ping Li, J., Asim Saleem, M., Manogran, G., Kadry, S., Basit, A., & Attique Khan, M. (2021). A dynamic clustering technique based on deep reinforcement learning for Internet of vehicles. Journal of Intelligent Manufacturing, 32, 757–768.

    Article  Google Scholar 

  13. Bersali, M., Rachedi, A., & Bouarfa, H. (2020) A new collaborative clustering approach for the Internet of Vehicles (CCA-IoV). In Second international conference on embedded & distributed systems (EDiS). Algeria, 3 November.

  14. Ebadinezhad, S. (2021). Design and analysis of an improved AODV protocol based on clustering approach for Internet of Vehicles (AODV-CD). International Journal of Electronics and Telecommunications, 67(1), 13–22.

    Google Scholar 

  15. Senouci, O., Harous, S., & Aliouat, Z. (2018) An efficient weight-based clustering algorithm using mobility report for IoV. In 9th IEEE annual ubiquitous computing, electronics & mobile communication conference (UEMCON), 8–10 November.

  16. Hande, R. S., & Muddana, A. (2016). Comprehensive survey on clustering-based efficient data dissemination algorithms for VANET. In IEEE, international conference on signal processing, communication, power and embedded system (SCOPES). Paralakhemundi.

  17. Sood, M., & Kanwar, S. (2014). Clustering in MANET and VANET: A survey. In International conference on circuits, systems, communication and information technology applications (CSCITA). Mumbai.

  18. Luo, Y., Zhang, W., & Hu, Y. (2010) A new cluster based routing protocol for VANET. In IEEE international conference on networks security wireless communications and trusted computing (NSWCTC) (pp. 176–180). China.

  19. Huang, Z., Por, L. Y., Ang, T. F., Anisi, M. H., & Adam, M. S. (2019). Improving the accuracy rate of link quality estimation using fuzzy logic in mobile wireless sensor network. Advances in Fuzzy Systems, 2019, 3478027.

    Article  Google Scholar 

  20. Hu, X., Ma, L., Ding, Y., Xu, J., Li, Y., & Ma, S. (2019). Fuzzy logic-based geographic routing protocol for dynamic wireless sensor networks. Sensors, 19(1), 196. https://doi.org/10.3390/s19010196

    Article  Google Scholar 

  21. Mishra, A. K., Kumar, R., & Singh, J. (2015). A review on fuzzy logic based clustering algorithms for wireless sensor networks. In IEEE international conference on futuristic trends on computational analysis and knowledge management. Noida.

  22. Balakrishnan, B., & Balachandran, S. (2017). FLECH: Fuzzy logic based energy efficient clustering hierarchy for nonuniform wireless sensor networks. Wireless Communications and Mobile Computing, 2017, 13.

    Article  Google Scholar 

  23. Wang, Q., Lin, D., Yang, P., & Zhang, Z. (2018). A fuzzy-logic based energy-efficient clustering algorithm for the wireless sensor networks. In Proceedings—SoftCOM 2018: 26th international conference on software, telecommunications and computer networks. x, Split, Croatia. IEEE. ISBN 978-9-5329-0087-3, 2015.

  24. Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353.

    Article  MathSciNet  MATH  Google Scholar 

  25. Tamir, D. E., Rishe, N. D., & Kandel, A. (2015). Fifty Years of Fuzzy Logic and its Applications. Springer. ISBN 978-3-319-19683-1.

    Book  MATH  Google Scholar 

  26. Ross, T. J. (2010). Fuzzy logic with engineering applications, Third edition. Wiley. ISBN 978-0-470-74376-8.

    Book  Google Scholar 

  27. Shelly, S., & Babu, A. V. (2017). Link residual lifetime-based next hop selection scheme for vehicular ad hoc networks. EURASIP Journal on Wireless Communications and Networking, 2017(1), 1–13.

    Article  Google Scholar 

  28. Huang, J., & Bai, J. (2008) A novel approach of link availability estimation for mobile ad hoc networks. In IEEE conference: vehicular technology conference. VTC Spring

  29. Alsharif, N., Aldubaikhy, K., & Shen. X. (2016). Link duration estimation using neural networks based mobility prediction in vehicular networks. In IEEE Canadian conference on electrical and computer engineering (CCECE).

  30. Sofra, N., Gkelias, A., & Leung, K. K. (2011). Route construction for long lifetime in VANETs. IEEE Transactions on Vehicular Technology, 60(7), 3450–3461.

    Article  Google Scholar 

  31. Riley, G. F., & Henderson, T. R. (2010). The ns-3 network simulator. In K. Wehrle, M. Güneş, & J. Gross (Eds.), Modeling and tools for network simulation. Springer.

    Google Scholar 

  32. Karnadi, F. K., Mo, Z. H., & Lan, K. C. (2007). Rapid generation of realistic mobility models for VANET. In Proceedings of IEEE wireless communications and networking conference (pp. 2506–2511).

  33. Lakas, A., Fekair, M., Korichi, A., & Lagraa, N. (2019). A multiconstrained QoS-compliant routing scheme for highway-based vehicular networks. Wireless Communications and Mobile Computing, 2019, 4521859.

    Article  Google Scholar 

  34. Abada, D., Massaq, A., & Boulouz, A. (2017). Improving routing performances to provide internet connectivity in VANETs over IEEE 802.11p. International Journal of Advanced Computer Science and Applications. https://doi.org/10.14569/IJACSA.2017.080472

    Article  Google Scholar 

  35. Gasmi, R., & Harous, S. (2022). Robust connectivity-based internet of vehicles clustering algorithm. Wireless Personal Communications, 125, 3153–3185.

    Article  Google Scholar 

Download references

Funding

This research work is supported by PHC-Tassili Grant Number 17MDU984.

Author information

Authors and Affiliations

  1. Faculty of Sciences, University Center of Illizi, Illizi, Algeria

    Rim Gasmi

  2. Faculty of Sciences, Ferhat Abbas University Setif 1, LRSD, Setif, Algeria

    Makhlouf Aliouat & Zibouda Aliouat

  3. University of Lyon CNRS Lyon 1, LIRIS, Lyon, France

    Hamida Seba

Authors
  1. Rim Gasmi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Makhlouf Aliouat
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zibouda Aliouat
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hamida Seba
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to the study conception and design. The first draft of the manuscript was written by RG and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Rim Gasmi.

Ethics declarations

Conflict of interest

The authors declare that there is no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gasmi, R., Aliouat, M., Aliouat, Z. et al. Routing Protocol Based Quality of Service and Links Stability (RPQLS) for Future Internet of Vehicles. Wireless Pers Commun 130, 2013–2038 (2023). https://doi.org/10.1007/s11277-023-10369-5

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-023-10369-5

Keywords

Search

Navigation