IDTracS: an Interest-Data-flow tracking-based forwarding scheme for vehicular named data networks | The Journal of Supercomputing
Skip to main content
Springer Nature Link
Log in

IDTracS: an Interest-Data-flow tracking-based forwarding scheme for vehicular named data networks

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

The vehicular named data networking (VNDN) is gaining more attention as a future vehicular networking (VN) model. The VNDN's fundamental principles of data naming, data-centric forwarding, and in-network caching make it inherently capable of mitigating the challenges in traditional VN. However, broadcast communication for content discovery and delivery causes VNDN to face challenges such as overhead due to packets redundancy, collision, and retransmission. In this paper, we introduce an Interest-Data-flow tracking-based forwarding scheme (IDTracS) for VNDN. IDTracS aims to improve VNDN performance by prioritizing the potential best forwarders and addressing Interest and Data packet broadcast issues. IDTracS is a receiver- and time-contention-based forwarding scheme that controls both Interest and Data packets forwarding. IDTracS uses the node’s degree of centrality to the Interest/Data flow and the node’s geo-distance closeness from the last Interest/Data forwarder for the requested content name-prefix. Accordingly, it computes an Interest/Data forwarding delay timer for prioritizing Interest/Data among nodes. The simulation findings reveal that the proposed IDTracS achieves an enhanced Interest satisfaction ratio, delivery delay and network transmission overhead compared to related geo-position- and distance-based protocols.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Japan)

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

Similar content being viewed by others

Availability of data and materials

Not applicable.

References

  1. Singh PK, Nandi SK, Nandi S (2019) A tutorial survey on vehicular communication state of the art, and future research directions. Veh Commun 18:100164. https://doi.org/10.1016/j.vehcom.2019.100164

    Article  Google Scholar 

  2. Zhang L, Afanasyev A, Burke J et al (2014) Named data networking. ACM SIGCOMM Comput Commun Rev 44:66–73. https://doi.org/10.1145/2656877.2656887

    Article  Google Scholar 

  3. Al-Omaisi H, Sundararajan EA, Alsaqour R et al (2021) A survey of data dissemination schemes in vehicular named data networking. Veh Commun 30:1003. https://doi.org/10.1016/j.vehcom.2021.100353

    Article  Google Scholar 

  4. Niari AK, Berangi R, Fathy M (2018) ECCN: an extended CCN architecture to improve data access in vehicular content-centric network. J Supercomput 74:205–221. https://doi.org/10.1007/s11227-017-2126-3

    Article  Google Scholar 

  5. Chen C, Wang C, Qiu T et al (2020) Caching in Vehicular Named Data Networking: Architecture, Schemes and Future Directions. IEEE Commun Surv Tutor. https://doi.org/10.1109/COMST.2020.3005361

    Article  Google Scholar 

  6. Al-Omaisi H, Sundararajan EA, Abdullah NF (2019) Towards VANET-NDN: a framework for an efficient data dissemination design scheme. In: 2019 International Conference on Electrical Engineering and Informatics (ICEEI). IEEE, pp 412–417. https://doi.org/10.1109/ICEEI47359.2019.8988843

  7. Kuai M, Hong X, Flores RR (2014) Evaluating interest broadcast in vehicular named data networking. In: 2014 Third GENI Research and Educational Experiment Workshop. IEEE, pp 77–78

  8. Al-Omaisi H, Sundararajan EA, Alsaqour R et al (2023) GeoISA: A new road-topology-assisted geo-based content discovery scheme for vehicular named data networking. Veh Commun 40:100573. https://doi.org/10.1016/j.vehcom.2023.100573

    Article  Google Scholar 

  9. Guo X, Chen Y, Cao L et al (2020) A receiver-forwarding decision scheme based on Bayesian for NDN-VANET. China Commun 17:106–120. https://doi.org/10.23919/JCC.2020.08.009

    Article  Google Scholar 

  10. Ahmed SH, Bouk SH, Kim D (2015) RUFS: RobUst forwarder selection in vehicular content-centric networks. IEEE Commun Lett 19:1616–1619. https://doi.org/10.1109/LCOMM.2015.2451647

    Article  Google Scholar 

  11. Boukerche A, Coutinho RWL (2019) LoICen: A novel location-based and information-centric architecture for content distribution in vehicular networks. Ad Hoc Netw 93:101899. https://doi.org/10.1016/j.adhoc.2019.101899

    Article  Google Scholar 

  12. Chowdhury M, Khan JA, Wang L (2020) Leveraging content connectivity and location awareness for adaptive forwarding in NDN-based mobile ad hoc networks. In: Proceedings of the 7th ACM Conference on Information-Centric Networking. ACM, New York, NY, USA, pp 59–69. https://doi.org/10.1145/3405656.3418713

  13. de Sousa AM, Araujo FRC, Sampaio LN (2018) A link-stability-based interest-forwarding strategy for vehicular named data networks. IEEE Internet Comput 22:16–26. https://doi.org/10.1109/MIC.2018.032501512

    Article  Google Scholar 

  14. Li D, Song T, Yang Y, Ul IR (2020) A reliable and efficient forwarding strategy in vehicular named data networking. J Commun Netw 22:348–357. https://doi.org/10.1109/JCN.2020.000014

    Article  Google Scholar 

  15. Ahmed SH, Bouk SH, Yaqub MA et al (2016) CODIE: controlled data and interest evaluation in vehicular named data networks. IEEE Trans Veh Technol 65:3954–3963. https://doi.org/10.1109/TVT.2016.2558650

    Article  Google Scholar 

  16. Amadeo M, Campolo C, Molinaro A (2015) Forwarding strategies in named data wireless ad hoc networks: design and evaluation. J Netw Comput Appl 50:148–158. https://doi.org/10.1016/j.jnca.2014.06.007

    Article  Google Scholar 

  17. Grassi G, Pesavento D, Pau G et al (2014) VANET via named data networking. In: 2014 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). IEEE, pp 410–415

  18. Wang L, Afanasyev A, Kuntz R et al (2012) Rapid traffic information dissemination using named data. In: Proceedings of the 1st ACM Workshop on Emerging Name-Oriented Mobile Networking Design - Architecture, Algorithms, and Applications - NoM’12. ACM Press, New York, New York, USA, p 7

  19. Yu X, Coutinho RWL, Boukerche A, Loureiro AAF (2017) A distance-based interest forwarding protocol for vehicular information-centric networks. In: 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC). IEEE, pp 1–5. https://doi.org/10.1109/PIMRC.2017.8292229

  20. Rondon LB, da Costa JBD, Filho GPR, Villas LA (2019) A distance and position-based caching discovery protocol for vehicular named-data networks. In: 2019 IEEE Latin-American Conference on Communications (LATINCOM). IEEE, pp 1–6. https://doi.org/10.1109/LATINCOM48065.2019.8938022

  21. Zafar WUI, Rehman MAU, Jabeen F et al (2021) Context-aware naming and forwarding in NDN-based VANETs. Sensors 21:4629. https://doi.org/10.3390/s21144629

    Article  Google Scholar 

  22. Prates AA, Bastos IV, Moraes IM (2019) GeoZone: An interest-packet forwarding mechanism based on dissemination zone for content-centric vehicular networks. Comput Electr Eng 73:155–166. https://doi.org/10.1016/j.compeleceng.2018.11.015

    Article  Google Scholar 

  23. Rondon LB, Immich R, Filho GPR et al (2020) Towards improved vehicular information-centric networks by efficient caching discovery. Vehicles 2:453–467. https://doi.org/10.3390/vehicles2030025

    Article  Google Scholar 

  24. Ali I, Lim H (2021) NameCent: name centrality-based data broadcast mitigation in vehicular named data networks. IEEE Access 9:162438–162447. https://doi.org/10.1109/ACCESS.2021.3133016

    Article  Google Scholar 

  25. Amadeo M, Campolo C, Ruggeri G et al (2020) Caching transient contents in vehicular named data networking: a performance analysis. Sensors 20:1–17. https://doi.org/10.3390/s20071985

    Article  Google Scholar 

  26. Shi J, Zhang B (2012) NDNLP: a link protocol for NDN. NDN Team, NDN, Technical Report NDN-0006 1–15

  27. Tourani R, Misra S, Mick T, Panwar G (2018) Security, privacy, and access control in information-centric networking: a survey. IEEE Commun Surv Tutor 20:566–600. https://doi.org/10.1109/COMST.2017.2749508

    Article  Google Scholar 

  28. Khelifi H, Luo S, Nour B, Shah SC (2018) Security and privacy issues in vehicular named data networks: an overview. Mob Inf Syst 2018:1–11. https://doi.org/10.1155/2018/5672154

    Article  Google Scholar 

  29. Ji X, Xu W, Zhang C et al (2019) Keep forwarding path freshest in VANET via applying reinforcement learning. In: 2019 IEEE First International Workshop on Network Meets Intelligent Computations (NMIC). IEEE, pp 13–18. https://doi.org/10.1109/NMIC.2019.00008

  30. Purkait R, Tripathi S (2020) Fuzzy logic based multi-criteria intelligent forward routing in VANET. Wirel Pers Commun 111:1871–1897. https://doi.org/10.1007/s11277-019-06962-2

    Article  Google Scholar 

  31. Mastorakis S, Afanasyev A, Zhang L (2017) On the evolution of ndnSIM. ACM SIGCOMM Comput Commun Rev 47:19–33. https://doi.org/10.1145/3138808.3138812

    Article  Google Scholar 

  32. Lopez PA, Wiessner E, Behrisch M et al (2018) Microscopic traffic simulation using SUMO. In: 2018 21st International Conference on Intelligent Transportation Systems (ITSC). IEEE, pp 2575–2582. https://doi.org/10.1109/ITSC.2018.8569938

  33. Li Y, Shi X, Lindgren A et al (2018) Context-aware data dissemination for ICN-based vehicular ad hoc networks. Information 9:263. https://doi.org/10.3390/info9110263

    Article  Google Scholar 

  34. Tizvar R, Abbaspour M (2020) A density-aware probabilistic interest forwarding method for content-centric vehicular networks. Veh Commun 23:100216. https://doi.org/10.1016/j.vehcom.2019.100216

    Article  Google Scholar 

  35. Magaia N, Francisco AP, Pereira P, Correia M (2015) Betweenness centrality in delay tolerant networks: a survey. Ad Hoc Netw 33:284–305. https://doi.org/10.1016/j.adhoc.2015.05.002

    Article  Google Scholar 

  36. Duarte JM, Kalogeiton E, Soua R et al (2018) A multi-pronged approach to adaptive and context aware content dissemination in VANETs. Mobile Netw Appl 23:1247–1259. https://doi.org/10.1007/s11036-017-0816-y

    Article  Google Scholar 

  37. Zhang Y, Wang J, Gong L et al (2017) A quantified forwarding strategy in NDN by integrating ant colony optimization into MADM. In: 2017 IEEE International Symposium on Parallel and Distributed Processing with Applications and 2017 IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC). IEEE, pp 214–220. https://doi.org/10.1109/ISPA/IUCC.2017.00039

  38. Shahwani H, Attique Shah S, Ashraf M et al (2022) A comprehensive survey on data dissemination in vehicular ad hoc networks. Veh Commun 34:100420. https://doi.org/10.1016/j.vehcom.2021.100420

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank the support by Universiti Kebangsaan Malaysia (UKM), Research Encouragement Fund (GGP-2020-021), Princess Nourah bint Abdulrahman University Researchers Supporting Project Number (PNURSP2023R97), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia, and Ministry of Education, Malaysia, Grant (FRGS/1/2018/ICT03/UKM/02/3).

Funding

This work was funded by Universiti Kebangsaan Malaysia (UKM), Research Encouragement Fund (GGP-2020-021). In addition, this research was supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project Number (PNURSP2023R97), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. Furthermore, it was partially funded by the Ministry of Education, Malaysia, Fundamental Research Grant Scheme (FRGS/1/2018/ICT03/UKM/02/3).

Author information

Authors and Affiliations

  1. Centre for Software Technology and Management, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), 43600, Bangi, Malaysia

    Hussein Al-Omaisi & Elankovan A. Sundararajan

  2. Department of Information Technology, College of Computing and Informatics, Saudi Electronic University, P.O. Box 93499, Riyadh, 11673, Saudi Arabia

    Raed Alsaqour

  3. Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia (UKM), 43600, Bangi, Malaysia

    Nor Fadzilah Abdullah

  4. Center for Cyber Security, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), 43600, Bangi, Malaysia

    Khairul Azmi Abu Bakar

  5. Department of Information Technology, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia

    Maha Abdelhaq

Authors
  1. Hussein Al-Omaisi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Elankovan A. Sundararajan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Raed Alsaqour
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Nor Fadzilah Abdullah
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Khairul Azmi Abu Bakar
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Maha Abdelhaq
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

HA, EAS contributed to conceptualization; HA, EAS contributed to methodology; HA contributed to software; RA, NFA, MA were involved in the validation; HA assisted in writing—original draft preparation; EAS, RA, NFA, KAAB, MA helped in writing—review and editing; KAAB, NFA, MA acquired the funding; EAS, NFA contributed to resources; EAS, RA, NFA contributed to the supervision. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Elankovan A. Sundararajan.

Ethics declarations

Ethical approval

Not applicable.

Conflict of interest

The authors declare that they have 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

Al-Omaisi, H., Sundararajan, E.A., Alsaqour, R. et al. IDTracS: an Interest-Data-flow tracking-based forwarding scheme for vehicular named data networks. J Supercomput 79, 16580–16615 (2023). https://doi.org/10.1007/s11227-023-05268-2

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-023-05268-2

Keywords

Search

Navigation