Multi-QoS and Interference Concerned Reliable Routing in Military Information System

  • V. Vignesh
  • K. Premalatha
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 645)


Secured and trustable routing in military information system is a sophisticated task in which sharing of information with no distortion or collusion is important. Mobile ad hoc networking enables the military communication by forwarding the information to the corresponding nodes on the right time. In the available system, Neighborhood-based Interference-Aware (NIA) routing is performed over an environment of stabilized position node. This research cannot offer support to the military communication system where the troops of soldiers might have to move to different positions. This issue is resolved in the new research strategy by implementing the new framework known as Multi-Objective concerned Reliable Routing in Dynamic MANET (MORR-MANET). In this technical work, optimal routing is performed with due consideration to different QoS parameters making use of pareto-optimal approach. Once the optimal route path is found, interference is prevented through the monitoring of the information regarding the neighborhood. Moreover, this research work is also related to the path breakage due to the resource unavailability or node mobility, as observed in this research work making use of Modified Go-Back-N ARQ technique. The whole research is realized and thereafter shown in the simulation environment, and it is revealed that the proposed research methodology provides a better result, in comparison with the previous research work NIA. The proposed technique indicates better performance in terms of 13% better residual energy, 7% larger the number of live nodes, 13% least relative error compared to the available technique NIA.


Military communication Priority information QoS satisfaction Bandwidth allocation 


  1. 1.
    IHS Jane’s Military Communications Retrieved 2012-01-23Google Scholar
  2. 2.
    Bollobás, B.: Modern graph theory Springer Science & Business Media, vol. 184 (2013)Google Scholar
  3. 3.
    Zhang, X.M., Zhang, Y., Yan, F., Vasilakos, A.V.: Interference-based topology control algorithm for delay-constrained mobile ad hoc networks. IEEE Trans. Mob. Comput. 14(4), 742–754 (2015)CrossRefGoogle Scholar
  4. 4.
    Sultan, N.T., Jamieson, D.D., Simpson, V.A.: U.S. Patent No. 7, 831,733. Washington, DC: U.S. Patent and Trademark Office (2010)Google Scholar
  5. 5.
    Ahn, C.W., Ramakrishna, R.S.: A genetic algorithm for shortest path routing problem and the sizing of populations. IEEE Trans Evol Comput. vol. 6, no. 6, pp. 566–579 (2002)Google Scholar
  6. 6.
    Jamwal, D., Sharma, K.K., Chauhan, S.: Zone Routing Protocol (2014)Google Scholar
  7. 7.
    Lee, S.J., Gerla, M:. Dynamic load-aware routing in ad hoc networks. In: International Conference on Communications, vol. 10, pp. 3206–3210 (2001)Google Scholar
  8. 8.
    Rexford, J.L., Shaikh, A:. U.S. Patent No. 6, 801, 502. Washington, DC: U.S. Patent and Trademark Office (2004)Google Scholar
  9. 9.
    Zafar, H.: QoS-aware Multipath Routing Scheme for Mobile Ad Hoc Networks. Int J Commun Netw Inf Secur 4, 1–10 (2012)Google Scholar
  10. 10.
    Singh, J.P:. Delay prediction in mobile ad hoc network using artificial neural network. Proced. Technol. 4, 201–206 (2012)Google Scholar
  11. 11.
    Surjeet, B.: QoS bandwidth estimation scheme for delay sensitive applications in MANETs. J. Commun. Netw. Sci. Res. 5, 1–8 (2013)Google Scholar
  12. 12.
    Wang, J:. QoS routing with mobility prediction in MANET. In: Proceedings of the IEEE Pacific Rim Conference on Computers and Signal Processing, Victoria, BC, Canada, pp. 357–360 (2001)Google Scholar
  13. 13.
    Ting, C.K., Liao, C.C.: A memetic algorithm for extending wireless sensor network lifetime. Inf. Sci. 180(24), 4818–4833 (2010)CrossRefGoogle Scholar
  14. 14.
    Abdulla, A.E., Nishiyama, H., Kato, N.: Extending the lifetime of wireless sensor networks: a hybrid routing algorithm. Comput. Commun. 35(9), 1056–1063 (2012)CrossRefGoogle Scholar
  15. 15.
    Behdani, B., Yun, Y.S., Smith, J.C., Xia, Y.: Decomposition algorithms for maximizing the lifetime of wireless sensor networks with mobile sinks. Comput. Oper. Res. 39(5), 1054–1061 (2012)CrossRefzbMATHGoogle Scholar

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© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of ITSri Ramakrishna Engineering CollegeCoimbatoreIndia
  2. 2.Department of CSEBannari Amman Institute of TechnologySathyamangalamIndia

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