[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content

Advertisement

Springer Nature Link
Log in

F-Ant: an effective routing protocol for ant colony optimization based on fuzzy logic in vehicular ad hoc networks

  • Original Article
  • Published:
Neural Computing and Applications Aims and scope Submit manuscript

Abstract

Vehicular ad hoc networks (VANETs) are a subset of mobile ad hoc networks that provide communication services between nearby vehicles and also between vehicles and roadside infrastructure. These networks improve road safety and accident prevention and provide entertainment for passengers of vehicles. Due to the characteristics of VANET such as self-organization, dynamic nature and fast-moving vehicles, routing in this network is a considerable challenge. Swarm intelligence algorithms (nature-inspired) such as ant colony optimization (ACO) have been proposed for developing routing protocols in VANETs. In this paper, we propose an enhanced framework for ACO protocol based on fuzzy logic for VANETs. To indicate the effectiveness and performance of our proposed protocol, the network simulator NS-2 is used for simulation. The simulation results demonstrate that our proposed protocol achieves high data packet delivery ratio and low end-to-end delay compared to traditional routing algorithms such as ACO and ad hoc on-demand distance vector (AODV).

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
£29.99 /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 (United Kingdom)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Al-Sultan S, Al-Doori MM, Al-Bayatti AH, Zedan H (2014) A comprehensive survey on vehicular Ad Hoc network. J Netw Comput Appl 37:380–392

    Article  Google Scholar 

  2. Mokhtar B, Azab M (2015) Survey on security issues in vehicular ad hoc networks. J Alex Eng. doi:10.1016/j.aej.2015.07.011

    Google Scholar 

  3. http://www.vanet.mdx.ac.uk

  4. Li F, Wang Y (2007) Routing in vehicular ad hoc networks: a survey. J IEEE Veh Technol Mag 2:12–22

    Article  Google Scholar 

  5. Sharef BT, Alsaqour RA, Ismail M (2014) Vehicular communication ad hoc routing protocols: a survey. J Netw Comput Appl 40:363–396

    Article  Google Scholar 

  6. Perkins CE, Bhagwat P (1994) Highly dynamic destination-sequenced distance-vector routing (DSDV) for mobile computers. J ACM SIGCOMM Comput Commun Rev 24:234–244

    Article  Google Scholar 

  7. Clausen T, Hansen G, Christensen L, Behrmann G (2001) The optimized link state routing protocol, evaluation through experiments and simulation. In: Proceedings of the IEEE symposium on wireless personal mobile communications

  8. Santa J, Tsukada M, Ernst T, Mehani O, Gómez-Skarmeta AF (2009) Assessment of VANET multi-hop routing over an experimental platform. Int J Internet Protoc Technol 4:158–172

    Article  Google Scholar 

  9. Perkins CE, Royer EM (1999) Ad hoc on-demand distance vector routing. In: Proceedings of the 2nd IEEE workshop on mobile computing systems and applications, WMCSA’99, pp 90–100

  10. Johnson DB, Maltz DA (1996) Dynamic source routing in ad hoc wireless networks. J Mob Comput 353:153–181

    Article  Google Scholar 

  11. Dong H, Zhao X, Qu L, Chi X, Cui X (2014) Multi-hop routing optimization method based on improved ant algorithm for vehicle to roadside network. J Bionic Eng 11:490–496

    Article  Google Scholar 

  12. Jabbarpour MR, Jalooli A, Shaghaghi E, Noor RM, Rothkrantz L, Khokhar RH, Anuar NB (2014) Ant-based vehicle congestion avoidance system using vehicular networks. J Eng Appl Artif Intell 36:303–319

    Article  Google Scholar 

  13. Souza AB, Celestino J, Xavier FA, Oliveira FD, Patel A, Latifi M (2013) Stable multicast trees based on ant colony optimization for vehicular ad hoc network. In: Proceedings of international conference on information networking (ICOIN'13), pp 101–6

  14. Kayacan E, Ahmadieh Khanesar M (2016) Fuzzy neural networks for real time control applications. Elsevier, Amsterdam

    MATH  Google Scholar 

  15. Zadeh LA (1965) Fuzzy sets. J Inf Control 8:338–353

    Article  MATH  Google Scholar 

  16. Zadeh LA (2001) Fuzzy logic toolbox for use with MATLAB. The MathWorks, Inc., Natick

    Google Scholar 

  17. Kuchaki Rafsanjani M, Fatemidokht H (2015) FBeeAdHoc: a secure routing protocol for BeeAdHoc based on fuzzy logic in MANETs. Int J Electron Commun (AEÜ) 69:1613–1621

    Article  Google Scholar 

  18. http://en.wikipedia.org/wiki/Bandwidth (computing)

  19. Chatterjee S, Das S (2015) Ant colony optimization based enhanced dynamic source routing algorithm for mobile Ad hoc network. J Inf Sci 295:67–90

    Article  MathSciNet  Google Scholar 

  20. Dorigo M, Caro GD (1999) Ant colony optimization: a new meta-heuristic. In: Proceedings of the 1999 congress on evolutionary computation (CEC 99), Washington

  21. Godbole V (2012) Performance analysis of bio-inspired routing protocols based on random waypoint mobility model. J Def S & T Tech Bull Sci Res Technol Inst Def (STRIDE) 5:114–134

    Google Scholar 

  22. Krajzewicz D, Erdmann J, Behrisch M, Bieker L (2012) Recent development and applications of SUMO—simulation of urban mobility. Int J Adv Syst Meas 5:128–138

    Google Scholar 

Download references

Acknowledgement

The authors would like to express their thanks to the anonymous referees for their comments and suggestions which improved the paper.

Author information

Authors and Affiliations

  1. Department of Applied Mathematics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran

    Hamideh Fatemidokht

  2. Department of Computer Science, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran

    Marjan Kuchaki Rafsanjani

Authors
  1. Hamideh Fatemidokht
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Marjan Kuchaki Rafsanjani
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Marjan Kuchaki Rafsanjani.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fatemidokht, H., Kuchaki Rafsanjani, M. F-Ant: an effective routing protocol for ant colony optimization based on fuzzy logic in vehicular ad hoc networks. Neural Comput & Applic 29, 1127–1137 (2018). https://doi.org/10.1007/s00521-016-2631-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00521-016-2631-y

Keywords

Search

Navigation