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Wireless Networks

, Volume 21, Issue 4, pp 1181–1192 | Cite as

Cognitive cross-layer multipath probabilistic routing for cognitive networks

  • Deepti SinghalEmail author
  • Rama Murthy Garimella
Article

Abstract

Mobile Ad-hoc NETworks (MANETs) is a set of mobile nodes that can move around arbitrarily, and communicate with others in a multi-hop fashion without any assistance of base stations. With recent advances in Cognitive Radio (CR) technology, it is possible to apply the Dynamic Spectrum Access model in MANETs. This introduces the concept of Cognitive Radio Ad Hoc Networks (CRAHNs). Applying CR techniques provides better throughput, even in congested spectrum along with better propagation characteristics. CRAHN is a kind of intelligent network that is aware of its surrounding environment, and adapts to the transmission or reception parameters to achieve efficient communication without interfering with primary users. Routing in CR environment is a challenging task as the availability of channel is constrained by the presence of primary user. The problem of routing in CRAHNs targets the creation and maintenance of wireless multi-hop paths among cognitive nodes by deciding both the spectrum to be used and the relay nodes of the path. This paper proposes a cognitive cross-layer multipath probabilistic routing for cognitive radio based networks. The proposed solution uses spectrum holes identified by MAC layer, decides the channel to be used and transmit power level for each hop in the path. The proposed solution is implemented in NS2, and performance of the proposed solution is compared with the existing solution from the literature. The paper also shows that the proposed solution outperforms existing solution in terms of packet delivery ratio, average end-to-end delay and energy consumed per data packet.

Keywords

Cognitive radio Ad hoc networks Cross layer design Routing protocols 

References

  1. 1.
    Federal Communications Commission. (2002). FCC report of the spectrum efficiency working group. Resource document. FCC. http://www.fcc.gov/sptf/files/SEWGFinalReport_1.doc. Accessed 10 Nov 2014.
  2. 2.
    Wireless Telecommunications Bureau. (2000). FCC: Secondary Markets Initiative. http://wireless.fcc.gov/licensing/secondarymarkets/. Accessed 10 Nov 2014.
  3. 3.
    Mitola, J., & Maguire, G. Q, Jr. (1999). Cognitive radio: Making software radios more personal. Personal Communications, IEEE, 6(4), 13–18.CrossRefGoogle Scholar
  4. 4.
    Akyildiz, I. F., Lee, W.-Y., & Chowdhury, K. R. (2009). CRAHNs: Cognitive radio ad hoc networks. Ad Hoc Networks, 7(5), 810–836.CrossRefGoogle Scholar
  5. 5.
    Srivastava, V., & Motani, M. (2005). Cross-layer design: A survey and the road ahead. Communications Magazine, IEEE, 43(12), 112–119.CrossRefGoogle Scholar
  6. 6.
    Cacciapuoti, A.S., Calcagno, C., Caleffi, M., Paura, L. (2010). CAODV: Routing in mobile ad-hoc cognitive radio networks. In Wireless Days (WD), 2010 IFIP, p. 1–5.Google Scholar
  7. 7.
    Cacciapuoti, A. S., Caleffi, M., & Paura, L. (2012). Reactive routing for mobile cognitive radio ad hoc networks. Ad Hoc Networks, 10(5), 803–815.CrossRefGoogle Scholar
  8. 8.
    Li, B., Li, D., Wu, Q., Li, H. (2009). ASAR: Ant-based spectrum aware routing for cognitive radio networks. In Wireless Communications Signal Processing, 2009. WCSP 2009. International Conference on, p. 1–5.Google Scholar
  9. 9.
    Chowdhury, K. R., & Felice, M. D. (2009). Search: A routing protocol for mobile cognitive radio ad-hoc networks. Computer Communications, 32(18), 1983–1997.CrossRefGoogle Scholar
  10. 10.
    Chowdhury, K.R., Di Felice, M. (2009). SEARCH: A routing protocol for mobile cognitive radio ad-hoc networks. In Sarnoff Symposium, 2009. SARNOFF ’09. IEEE, p. 1–6.Google Scholar
  11. 11.
    Chowdhury, K. R., & Akyildiz, I. F. (2011). CRP: A routing protocol for cognitive radio ad hoc networks. Selected Areas in Communications, IEEE Journal on, 29(4), 794–804.CrossRefGoogle Scholar
  12. 12.
    Caleffi, M., Akyildiz, I. F., & Paura, L. (2012). OPERA: Optimal routing metric for cognitive radio ad hoc networks. Wireless Communications, IEEE Transactions on, 11(8), 2884–2894.Google Scholar
  13. 13.
    McCanne, S., & Floyd, S. (1997). The Network Simulator-Ns-2. Simulator Tool. Virtual InterNetwork Testbed Project. http://www.isi.edu/nsnam/ns/. Accessed 10 Nov 2014.
  14. 14.
    Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1(1), 269–271.CrossRefzbMATHMathSciNetGoogle Scholar
  15. 15.
    Bellman, R. (1958). On a routing problem. Quarterly of Applied Mathematics, 16(1958), 87–90.Google Scholar
  16. 16.
    Youssef, M., Ibrahim, M., Abdelatif, M., Chen, L., & Vasilakos, A. (2013). Routing metrics of cognitive radio networks: A survey. Communications Surveys Tutorials, IEEE, PP(99), 1–18.Google Scholar
  17. 17.
    Abdelaziz, S., & ElNainay, M. (2014). Metric-based taxonomy of routing protocols for cognitive radio ad hoc networks. Journal of Network and Computer Applications, 40, 151–163. doi: 10.1016/j.jnca.2013.09.001.
  18. 18.
    Marler, R. T., & Arora, J. S. (2004). Survey of multi-objective optimization methods for engineering. Structural and Multidisciplinary Optimization, 26(6), 369–395.CrossRefzbMATHMathSciNetGoogle Scholar
  19. 19.
    Miettinen, K. (1999). Nonlinear multiobjective optimization. Boston: Kluwer Academic Publishers.zbMATHGoogle Scholar
  20. 20.
    Di Felice, M., Chowdhury, K. R., Kim, W., Kassler, A., & Bononi, L. (2011). End-to-end protocols for cognitive radio ad hoc networks: An evaluation study. Performance Evaluation, 68(9), 859–875.CrossRefGoogle Scholar
  21. 21.
    Marina, M.K., Das, S.R. (2001). On-demand multipath distance vector routing in ad hoc networks. In Network Protocols, 2001. Ninth International Conference on, p. 14–23.Google Scholar
  22. 22.
    Banks, J., Carson, J. S., Nelson, B. L., & Nicol, D. M. (2000). Discrete-event system simulation (3rd ed.). New Jersey: Prentice Hall.Google Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.International Institute of Information TechnologyHyderabadIndia

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