Skip to main content
SpringerLink
Log in

An Adaptive Clustering Approach for Efficient Data Dissemination in IoV

  • Conference paper
  • First Online:
International Conference on Neural Computing for Advanced Applications (NCAA 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1870))

Included in the following conference series:

  • 380 Accesses

Abstract

Due to the inherent characteristics of Vehicular Ad-hoc Networks (VANETs), such as uneven distribution and high mobility, establishing and maintaining efficient routes for data dissemination is a significant and challenging issue. To enhance communication efficiency, many cluster-based protocols have been designed to reduce data redundancy and the number of control messages by integrating vehicles into manageable groups headed by a superior vehicle, known as the cluster head (CH). Nevertheless, most existing protocols are unable to adaptively adjust the cluster, resulting in a significant network burden and message transmission delay. To address this issue, we propose a cluster-based routing method empowered by Vehicle Fog Computing(VFC), which takes advantage of the clustering architecture to reduce the overhead of routing discovery and maintenance. Specifically, based on data transmission requirements and vehicle environment status, the proposed method can adaptively adjust the cluster structure and the number of CHs to reduce data redundancy and transmission load in concurrent scenarios of massive data transmission. Moreover, cooperating with the adaptive clustering method, a routing method is proposed to improve the efficiency of data transmission. Lastly, we conducted extensive experiments to verify the cluster-based routing scheme based on VFC. Our experimental results demonstrate that the proposed routing protocol is feasible and performs well compared to existing methods.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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. Arif, M., Wang, G., Bhuiyan, M.Z.A., Wang, T., Chen, J.: A survey on security attacks in VANETs: communication, applications and challenges. Veh. Commun. 19, 100179 (2019)

    Google Scholar 

  2. Liu, B., et al.: Collaborative intelligence enabled routing in green IOV: a grid and vehicle density prediction-based protocol. IEEE Trans. Green Commun. Netw. 7(2), 1012–1022 (2023)

    Article  MathSciNet  Google Scholar 

  3. Hussein, N.H., Yaw, C.T., Koh, S.P., Tiong, S.K., Chong, K.H.: A comprehensive survey on vehicular networking: communications, applications, challenges, and upcoming research directions. IEEE Access 10, 86127–86180 (2022)

    Article  Google Scholar 

  4. Dai, P., Hu, K., Wu, X., Xing, H., Teng, F., Yu, Z.: A probabilistic approach for cooperative computation offloading in MEC-assisted vehicular networks. IEEE Trans. Intell. Transp. Syst. 23(2), 899–911 (2020)

    Article  Google Scholar 

  5. Shao, X., Hasegawa, G., Dong, M., Liu, Z., Masui, H., Ji, Y.: An online orchestration mechanism for general-purpose edge computing. IEEE Trans. Serv. Comput. 16(2), 927–940 (2023)

    Article  Google Scholar 

  6. Liu, B., et al.: Multi-agent attention double actor-critic framework for intelligent traffic light control in urban scenarios with hybrid traffic. IEEE Trans. Mobile Comput. 1–13 (2023)

    Google Scholar 

  7. Dai, P., Han, B., Wu, X., Xing, H., Liu, B., Liu, K.: Distributed convex relaxation for heterogeneous task replication in mobile edge computing. IEEE Trans. Mobile Comput. 1–16 (2022)

    Google Scholar 

  8. Dai, P., Song, F., Liu, K., Dai, Y., Zhou, P., Guo, S.: Edge intelligence for adaptive multimedia streaming in heterogeneous internet of vehicles. IEEE Trans. Mobile Comput. (2021)

    Google Scholar 

  9. Liu, K., Xiao, K., Dai, P., Lee, V.C., Guo, S., Cao, J.: Fog computing empowered data dissemination in software defined heterogeneous VANETs. IEEE Trans. Mob. Comput. 20(11), 3181–3193 (2021)

    Article  Google Scholar 

  10. Liu, B., et al.: A novel V2V-based temporary warning network for safety message dissemination in urban environments. IEEE Internet Things J. 9(24), 25136–25149 (2022)

    Article  MathSciNet  Google Scholar 

  11. Liu, B., et al.: A region-based collaborative management scheme for dynamic clustering in green VANET. IEEE Trans. Green Commun. Netw. 6(3), 1276–1287 (2022)

    Article  MathSciNet  Google Scholar 

  12. Ayyub, M., Oracevic, A., Hussain, R., Khan, A.A., Zhang, Z.: A comprehensive survey on clustering in vehicular networks: current solutions and future challenges. Ad Hoc Networks (2021)

    Google Scholar 

  13. Perkins, C., Belding-Royer, E., Das, S.: Ad hoc on-demand distance vector (AODV) routing. Technical report (2003)

    Google Scholar 

  14. Mubarek, F.S., Aliesawi, S.A., Alheeti, K.M.A., Alfahad, N.M.: Urban-AODV: an improved AODV protocol for vehicular ad-hoc networks in urban environment (2018)

    Google Scholar 

  15. Zhang, D., Gong, C., Zhang, T., Zhang, J., Piao, M.: A new algorithm of clustering AODV based on edge computing strategy in IOV. Wirel. Netw. 27(4), 2891–2908 (2021). https://doi.org/10.1007/s11276-021-02624-z

    Article  Google Scholar 

  16. Karp, B.: GPSR: greedy perimeter stateless routing for wireless networks. In: ACM Mobicom (2000)

    Google Scholar 

  17. Alsarhan, A., Kilani, Y., Al-Dubai, A., Zomaya, A.Y., Hussain, A.: Novel fuzzy and game theory based clustering and decision making for VANETs. IEEE Trans. Veh. Technol. 69(2), 1568–1581 (2020)

    Article  Google Scholar 

  18. Kayis, O., Acarman, T.: Clustering formation for inter-vehicle communication. In: Intelligent Transportation Systems Conference (2007)

    Google Scholar 

  19. Khan, Z., Fang, S., Koubaa, A., Fan, P., Farman, H.: Street-centric routing scheme using ant colony optimization-based clustering for bus-based vehicular ad-hoc network. Comput. Elect. Eng. 86(1), 106736 (2020)

    Article  Google Scholar 

  20. Tseng, H.W., Wu, R.Y., Lo, C.W.: A stable clustering algorithm using the traffic regularity of buses in urban VANET scenarios. Wirel. Netw. 26(1), 2665–2679 (2020)

    Article  Google Scholar 

  21. He, C., Qu, G., Ye, L., Wei, S.: A two-level communication routing algorithm based on vehicle attribute information for vehicular ad hoc network. Wirel. Commun. Mob. Comput. 2021, 6692741:1–6692741:14 (2021)

    Google Scholar 

  22. Khan, Z., Fan, P., Fang, S., Abbas, F.: An unsupervised cluster-based VANET-oriented evolving graph (CVoEG) model and associated reliable routing scheme. IEEE Trans. Intell. Transp. Syst. 20(10), 3844–3859 (2019)

    Article  Google Scholar 

  23. Bine, L.M.S., Boukerche, A., Ruiz, L.B., Loureiro, A.A.F.: IoDSCF: a store-carry-forward routing protocol for joint bus networks and internet of drones. In: 2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS), pp. 950–960 (2022)

    Google Scholar 

  24. Malnar, M., Jevtic, N.: An improvement of AODV protocol for the overhead reduction in scalable dynamic wireless ad hoc networks. Wirel. Netw. 28(3), 1039–1051 (2022)

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by National Natural Science Foundation of China (No. 62272357), Key Research and Development Program of Hubei (No. 2022BAA052), Key Research and Development Program of Hainan (No. ZDYF2021GXJS014), Science Foundation of Chongqing of China (cstc2021jcyj-msxm4262), and Research Project of Chongqing Research Institute of Wuhan University of Technology (ZD2021-04, ZL2021-05).

Author information

Authors and Affiliations

  1. School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, 430070, China

    Weiyang Chen, Yuhao Liu, Yang Lu, Weizhen Han & Bingyi Liu

  2. Chongqing Research Institute, Wuhan University of Technology, Chongqing, 401135, China

    Weiyang Chen & Bingyi Liu

Authors
  1. Weiyang Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yuhao Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yang Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Weizhen Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Bingyi Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Weizhen Han .

Editor information

Editors and Affiliations

  1. Harbin Institute of Technology, Shenzhen, China

    Haijun Zhang

  2. Chaohu University, Hefei, China

    Yinggen Ke

  3. Chongqing University, Chongqing, China

    Zhou Wu

  4. South China Normal University, Guangzhou, China

    Tianyong Hao

  5. Hefei University of Technology, Hefei, China

    Zhao Zhang

  6. Technical University of Denmark, Kongens Lyngby, Denmark

    Weizhi Meng

  7. Chaohu University, Hefei, China

    Yuanyuan Mu

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Chen, W., Liu, Y., Lu, Y., Han, W., Liu, B. (2023). An Adaptive Clustering Approach for Efficient Data Dissemination in IoV. In: Zhang, H., et al. International Conference on Neural Computing for Advanced Applications. NCAA 2023. Communications in Computer and Information Science, vol 1870. Springer, Singapore. https://doi.org/10.1007/978-981-99-5847-4_28

Download citation

  • DOI: https://doi.org/10.1007/978-981-99-5847-4_28

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-5846-7

  • Online ISBN: 978-981-99-5847-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation