Advertisement

Distributed Multi-criteria Based Clusterhead Selection Approach for MANET

  • Preeti YadavEmail author
  • Ritu Prasad
  • Praneet SaurabhEmail author
  • Bhupendra Verma
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 922)

Abstract

Ad-hoc networks play an important role in situations where fixed wired pre-defined backbone cannot be created. In mobile adhoc network (MANET), discovery of routing path with minimum routing and control overhead are important challenges. In this paper, Distributed multi criteria based clustering approach (DMBCA) is introduced for overcoming routing overhead of network in mobile ad-hoc network. The proposed DBMCA use multiple metric clustering techniques for defining “optimal node factor” that can use in selection of cluster head. DMBCA is then compared with conventional AODV routing protocol in NS-2.35. Experimental results show that the proposed DMBCA achieves much better results in terms of performance parameters such as packet delivery ratio, average throughput and routing overhead than conventional AODV technique.

Keywords

MANET AODV Clusterhead NS-2.35 Weight based approach 

References

  1. 1.
    Feng, D., Zhu, Y., Luo, X.: Cooperative incentive mechanism based on game theory in MANET. In: ICNDS, pp. 201–204 (2009)Google Scholar
  2. 2.
    Wu, J.S., Huey, R.S.: A Routing Protocol using Game Theory in Wireless Ad Hoc Networks (2013)Google Scholar
  3. 3.
    Wu, L., Yu, R.: A threshold-based method for selfish nodes detection in MANET. In: Computer Symposium (ICS), pp. 875–882 (2010)Google Scholar
  4. 4.
    Buttyn, L., Hubaux, J.P.: Enforcing service availability in mobile ad-hoc WANs. In: Proceedings of the 1st ACM International Symposium on Mobile Ad Hoc Networking and Computing, pp. 87–96 (2000)Google Scholar
  5. 5.
    Marti, S., Giuli, T.J., Lai, K., Baker, M.: Mitigating routing misbehavior in mobile ad hoc networks. In: Proceedings of the 6th Annual International Conference on Mobile Computing and Networking, pp. 255–265 (2000)Google Scholar
  6. 6.
    Xu, Z., Wu, G., Xia, Q., Ren, J.: GTFTTS: a generalized tit-for-tat based corporative game for temperature-aware task scheduling in multi-core systems. In: Third International Symposium on Parallel Architectures, Algorithms and Programming (PAAP), pp. 81–88 (2010)Google Scholar
  7. 7.
    Tootaghaj, D.Z., Farhat, F., Pakravan, M.R., Aref, M.: Game-theoretic approach to mitigate packet dropping in wireless ad-hoc networks. In: Consumer Communications and Networking Conference (CCNC), pp. 163–165 (2011)Google Scholar
  8. 8.
    Usha, S., Radha, S.: Co-operative approach to detect misbehaving nodes in MANET using multi-hop acknowledgement scheme. In: Advances in Computing, Control, Telecommunication Technologies, pp. 576–578 (2009)Google Scholar
  9. 9.
    Komathy, K., Narayanasamy, P.: Study of co-operation among selfish neighbors in manet under evolutionary game theoretic model. In: Signal Processing, Communications and Networking, pp. 133–138 (2007)Google Scholar
  10. 10.
    Agarwal, R., Gupta, R., Motwani, M.: Performance optimisation through EPT-WBC in mobile ad hoc networks. Int. J. Electron. 103(3), 355–371 (2015)CrossRefGoogle Scholar
  11. 11.
    Bisen, D., Sharma, S.: An enhanced performance through agent-based secure approach for mobile ad hoc networks. Int. J. Electron. 105, 116–136 (2017)CrossRefGoogle Scholar
  12. 12.
    Thakur, N., Bisen, D., Gupta, N.: Proposed agent based black hole node detection algorithm for ad-hoc wireless network. Int. J. Comput. Sci. Appl. (IJCSA) 5(2), 69–85 (2015)Google Scholar
  13. 13.
    Saurabh, P., Verma, B.: An efficient proactive artificial immune system based anomaly detection and prevention system. Expert Syst. Appl. 60, 311–320 (2016)CrossRefGoogle Scholar
  14. 14.
    Saurabh, P., Verma, B.: Immunity inspired cooperative agent based security system. Int. Arab J. Inf. Technol. 15(2), 289–295 (2018)Google Scholar
  15. 15.
    Praneet, S., Verma, B., Sharma, S.: An immunity inspired anomaly detection system: a general framework. In: Bansal, J., Singh, P., Deep, K., Pant, M., Nagar, A. (eds.) BIC-TA 2012. Advances in Intelligent Systems and Computing, vol. 202. Springer, India (2013).  https://doi.org/10.1007/978-81-322-1041-2_36CrossRefGoogle Scholar
  16. 16.
    Saurabh, P., Verma, B., Sharma, S.: Biologically inspired computer security system: the way ahead. In: Thampi, S.M., Zomaya, A.Y., Strufe, T., Alcaraz Calero, J.M., Thomas, T. (eds.) SNDS 2012. CCIS, vol. 335, pp. 474–484. Springer, Heidelberg (2012).  https://doi.org/10.1007/978-3-642-34135-9_46CrossRefGoogle Scholar
  17. 17.
    Bisen, D., Suman, P., Sharma, S., Shukla, R.: Effect of pause time on DSR, AODV and DYMO routing protocols in MANET. Int. J. Inf. Technol. Knowl. Manag. 45–50 (2010). ISSN 0973-4414Google Scholar
  18. 18.
    Bisen, D., Sharma, S.: Improve performance of TCP new reno over mobile ad-hoc network using ABRA. Int. J. Wirel. Mob. Netw. (IJWMN) 3(2), 102–111 (2011). ISSN 0975-3834CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Technocrats Institute of Technology (Excellence)BhopalIndia
  2. 2.Technocrats Institute of TechnologyBhopalIndia

Personalised recommendations