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Cluster Computing

, Volume 22, Supplement 5, pp 12397–12409 | Cite as

Optimized dynamic source routing protocol for MANETs

  • N. PrasathEmail author
  • J. Sreemathy
Article
  • 105 Downloads

Abstract

Mobile ad-hoc networks (MANETs) are wireless networks comprising of small, battery powered mobile devices/nodes. All these nodes communicate cooperatively without fixed infrastructure and able to operate alone or in coordination with wired infrastructure by using gateway nodes. In this work, the performance of optimized dynamic source routing protocol (DSR) is investigated for MANETs. To find the optimal paths between the communicating nodes, traditional DSR algorithm is modified by using the Fire fly algorithm. In recent times a population based method named as Firefly algorithm is stimulated by the surveillance of real firefly and its brightness behaviour. So firefly algorithm is used for the proposed method on MANET which improves the DSR routing performance with well-organized packets transfer from the source to destination node. Optimal route is found based on link quality, node mobility and end to end delay. Simulations are conducted with 25 nodes and the performance of the traditional DSR, link quality based DSR for selecting a route and proposed firefly algorithm for optimal route finding are compared by the parameters such as throughput, end to end delay, number of retransmitted packets and the number of hops to the destination.

Keywords

MANET DSR Link quality Mobility and end to end delay Fire fly algorithm 

References

  1. 1.
    Buruha, S.: Introduction to wireless AdHoc Networks. http://www.comp.brad.ac.uk/sburuha1/wirelessadhoc.html (2017). Accessed 10 Nov 2017
  2. 2.
    Du, X., Zhao, Z.: A group key agree management scheme for MANET. Int. J. Nonlinear Sci. 10(1), 77–81 (2010)MathSciNetzbMATHGoogle Scholar
  3. 3.
    Mario, G., Xiaoyan, H.: Fisheye state routing protocol draft-ietf-manet-fsr-03.txt 55th IETF Meeting in Altanta, GA. (2004)Google Scholar
  4. 4.
    Samir, R., Perkins, D., Elizabeth, C.E., Royer, M.: Performance comparison of two on demand routing protocols for ad hoc network. In Proceedings of the INFOCOM, Tel Aviv, Israel (2000)Google Scholar
  5. 5.
    Pandey, A.K., Fujinoki, H.: Study of MANET routing protocols by GloMoSim simulator. Int. J. Netw. Manag. 15(6), 393–410 (2005)CrossRefGoogle Scholar
  6. 6.
    Johnson, D.B., Maltz, D.A., Broch, J.: DSR: The dynamic source routing protocol for multi-hop wireless ad hoc networks. Ad hoc Netw. 5, 139–172 (2001)Google Scholar
  7. 7.
    Al-Omari, S.A.K., Sumari, P.: An overview of mobile ad hoc networks for the existing protocols and applications. arXiv preprint arXiv:1003.3565 (2010)
  8. 8.
    Manickam, P., Baskar, T.G., Girija, M., Manimegalai, D.D.: Performance comparisons of routing protocols in mobile ad hoc networks. arXiv preprint arXiv:1103.0658 (2011)
  9. 9.
    Shrestha, A., Tekiner, F.: On MANET routing protocols for mobility and scalability. In : Proceedings of the 2009 International Conference on Parallel and Distributed Computing, Applications and Technologies, pp. 451–456 (2009)Google Scholar
  10. 10.
    Ya-qin, F., Wen-yong, F., Lin-zhu, W.: Opnet-based network of manet routing protocols dsr computer simulation. In: Proceedings of the 2010 WASE International Conference on Information Engineering (ICIE), IEEE, Vol. 4, pp. 46–49. (2010)Google Scholar
  11. 11.
    Asl, E.K., Damanafskan. M., Abbaspour, M., Noorhosseini. M.: MANETs based ant colony optimization. In: Proceedings of the Third International Conference on Modeling and Simulation, (2009)Google Scholar
  12. 12.
    Gargi, R., Chaba, Y., Patel, R.B.: Improving the performance of dynamic source routing protocol by optimization of neural networks. Int. J. Comput. Sci. Issues 9(4), 471–479 (2010)Google Scholar
  13. 13.
    Mamoun, M.H.: A proposed route selection technique in DSR routing protocol for MANET. Int. J. Eng. Technol. IJET-IJENS 11(02), 10–13 (2011)Google Scholar
  14. 14.
    Qaed, A.S., Devi, T.: Link Quality, delay and energy aware routing protocol (LQDEARP) for Mobile AD HOC Networks. Int. J. Comput. Commun. Technol. 4(1), 49–54 (2013)Google Scholar
  15. 15.
    Rao, S.P., Nagabhooshanam, E., Babu, S.R.: Quality of service routing in mobile Ad hoc networks using node mobility and energy depletion parameters. Int. J. Netw. Secur. Appl. 5(3), 1 (2013)Google Scholar
  16. 16.
    Upadhayaya, D.S., Gandhi, C.: Quality of service routing in mobile ad hoc networks using location and energy parameters. Int. J. Wirel. Mob. Netw. 1(2), 139–147 (2009)Google Scholar
  17. 17.
    Xu, M., Liu, G.: A multipopulation firefly algorithm for correlated data routing in underwater wireless sensor networks. Int. J. Distrib. Sens. Netw. 9(3), 1–11 (2013)Google Scholar
  18. 18.
    Swain, T., Pattnaik, P.K., Bounour, I.B.N., Movahednejad, H., Suhaimi, B.T., Sharifi, M., Ezhilmaran, D.: Performance of separated random user scheduling (SRUS) and jount user scheduling (JUS) in the long-term Evolution-Advanced. J. Theor. Appl. Inf. Technol. 59(1), 1–8 (2014)Google Scholar
  19. 19.
    Johnson, D., Hu, Y.C., Maltz, D.: The dynamic source routing protocol (DSR) for mobile ad hoc networks for IPv4 (No. RFC 4728) (2007)Google Scholar
  20. 20.
    Hu, Y.C., Johnson, D.B.: Caching strategies in on-demand routing protocols for wireless ad hoc networks. In: Proceedings of the 6th Annual International Conference on Mobile Computing and Networking, pp. 231–242 (2000)Google Scholar
  21. 21.
    Biswal, S., Mohanty, S., Seth, D.: Study of DSR Routing protocol in Mobile Adhoc network. In International Conference on Information and Network Technology, IACSIT Press, Singapore, IPCSIT, Vol. 4 (2011)Google Scholar
  22. 22.
    Yang, X.S.: Nature-Inspired Metaheuristic Algorithms. Luniver press, Sacramento (2010)Google Scholar
  23. 23.
    Yang, X.S., Deb, S.: Eagle strategy using Lévy walk and firefly algorithms for stochastic optimization. Nat. Insp. Cooper. Strat. Optim. 284, 101–111 (2010)zbMATHGoogle Scholar

Copyright information

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

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringKPR Institute of Engineering and TechnologyCoimbatoreIndia
  2. 2.Department of Computer Science and EngineeringSri Eshwar College of EngineeringCoimbatoreIndia

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