Semi-markov Process Based Cooperation Enforcement Mechanism for MANETs

Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 32)


Network Survivability is defined as the potential of the network to maintain its connectivity even during the event of failures and attacks. This network survivability is highly affected by the presence of selfish nodes in the ad hoc network. In this paper, we focus on developing a Semi-Markov Process based Cooperation Enforcement Model (SMPCEM) for isolating selfish nodes and further analyze the factors that affect network survivability through transition probability matrix derived from stochastic events. Furthermore, we examine the dynamic change in behavior of mobile nodes based on parameters like residual energy and packet delivery rate. Finally, we evaluate the proposed SMPCEM approach through simulation and numerical analysis. The simulation results make it evident that SMPCEM efficiently isolates selfish nodes and upholds the network survivability by increasing the packet delivery ratio and decreasing the end to end delay, drop rate, energy consumption when compared to Correlated Node Behavior Model (CNBM).


Semi-markov decision process Cooperation Selfish nodes Stochastic properties Network survivability Transition probability matrix 


  1. 1.
    Michiardi, P., Molva, R.: CORE: a collaborative reputation mechanism to enforce node coperationin mobile adhoc networks. Presented at Communication and Multimedia Security. Protoroz, Solvenia (2002)Google Scholar
  2. 2.
    Buchegger, S., Boudec, J.Y.: Nodes bearing grudges: towards routing security, fairness and robustness in mobile ad-hoc network. Presented at Tenth Eurominicro Workshop on Parallel, Distributed and Network Based Processing. Canary Islands, Spain (2002)Google Scholar
  3. 3.
    Marti, S., Giuli, T.J., Lai, K., Baker, M.: Mitigating routing misbehavior in mobile ad hoc networks. Mobile Comput. Networking 1, 255–265 (2000)Google Scholar
  4. 4.
    Hwang, S.K., Kim, D.S.: Markov model of link connectivity in mobile ad hoc networks. Telecommun. Syst. 34(1–2), 51–58 (2006)Google Scholar
  5. 5.
    Guang, L., Chadi, M., Benslimane, A.: Enhancing IEEE 802.11 random backoff in selfish environments. IEEE Trans. Veh. Technol. 57(3), 1806–1822 (2008)Google Scholar
  6. 6.
    Xing, F., Wang, W.: Modeling and analysis of connectivity in mobile ad hoc networks with misbehaving nodes. IEEE (2006)Google Scholar
  7. 7.
    Orallo, E., Serraty, M.D., Cano, J.C., Calafate, T., Manzoni, P.: Improving selfish node detection in MANETs using a collaborative watchdog. IEEE Lett. 16(5), 642–645 (2012)Google Scholar
  8. 8.
    Tang, J., Cheng, Y.: Selfish misbehavior detection in 802.11 based wireless networks. In: An Adaptive Approach Based on Markov Decision Process IEEE (2013)Google Scholar
  9. 9.
    Xing, F.: Modeling, Design, and Analysis on the Resilience of Large-scale Wireless Multi-hop Networks. University of North Carolina, North Carolina (2009)Google Scholar
  10. 10.
    Cárdenas, A.A., Radosavac, S., Baras, J.S.: Evaluation of detection algorithms for MAC layer misbehavior: theory and experiments. IEEE (2009)Google Scholar
  11. 11.
    Vallam, R.D., Franklin, A.A., Murthy, C.S.: Modelling co-operative MAC layer misbehaviour in IEEE 802.11 ad hoc networks with heterogeneous loads. IEEE (2008)Google Scholar
  12. 12.
    Komathy, K., Narayanasamy, P.: A probabilistic behavioral model for selfish neighbors in a wireless ad hoc network. IJCSNS 7(7), 77 (2007)Google Scholar
  13. 13.
    Wang, S., Park, J.T.: Modeling and analysis of multi-type failures in wireless body area networks with Semi-Markov model. Commun. Lett. IEEE. 14(1), 6–8 (2010)CrossRefGoogle Scholar
  14. 14.
    Patil, A.P., Rajanikanth, K., BatheySharanya, M.P., Kumar, D., Malavika, J.: Design of energy effiecient routing protocol for MANETs based on AODV. IJCSI 8(1), 215–220 (2011)Google Scholar
  15. 15.
    Akhtar, A.K. Md., Sahoo, G: Mathematical model for the detection of selfish nodes in MANETs. Int. J. Comput. Sci. Inform. 1(3), 25–28 (2008)Google Scholar
  16. 16.
    Sundarajan, T., Shanmugam, A.: Modeling the behavior of selfish forwarding nodes to simulate cooperation in MANET. Int. J. 2(2), 147–160 (2010)Google Scholar
  17. 17.
    Corradi, G., Janssen, J., Manca, R.: Numerical treatment of homogenous Semi-Markov rocesses in transient case—a straightforward approach. Methodol. Comput. Appl. Probab. 6, 233–246 (2004)CrossRefMathSciNetMATHGoogle Scholar
  18. 18.
    Sundarajan, T., Shanmugam, A.: Modeling the behavior of selfish forwarding nodes to simulate cooperation in MANET. Int. J. 2(2), 147–160 (2010)Google Scholar
  19. 19.
    Azni1, A.H., Ahmad, R., Zul, A. Md., Samad, A., Basari, H., Hussin, B.: Correlated node behavior model based on Semi Markov process for MANETS. IEEE (2013)Google Scholar

Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringPondicherry Engineering CollegePillaichavadyIndia

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