Skip to main content
Springer Nature Link
Log in

Cognitive cross-layer multipath probabilistic routing for cognitive networks

  • Published:
Wireless Networks Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

References

  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. Wireless Telecommunications Bureau. (2000). FCC: Secondary Markets Initiative. http://wireless.fcc.gov/licensing/secondarymarkets/. Accessed 10 Nov 2014.

  3. Mitola, J., & Maguire, G. Q, Jr. (1999). Cognitive radio: Making software radios more personal. Personal Communications, IEEE, 6(4), 13–18.

    Article  Google Scholar 

  4. Akyildiz, I. F., Lee, W.-Y., & Chowdhury, K. R. (2009). CRAHNs: Cognitive radio ad hoc networks. Ad Hoc Networks, 7(5), 810–836.

    Article  Google Scholar 

  5. Srivastava, V., & Motani, M. (2005). Cross-layer design: A survey and the road ahead. Communications Magazine, IEEE, 43(12), 112–119.

    Article  Google Scholar 

  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.

  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.

    Article  Google Scholar 

  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.

  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.

    Article  Google Scholar 

  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.

  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.

    Article  Google Scholar 

  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. 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. Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1(1), 269–271.

    Article  MATH  MathSciNet  Google Scholar 

  15. Bellman, R. (1958). On a routing problem. Quarterly of Applied Mathematics, 16(1958), 87–90.

  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. 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. Marler, R. T., & Arora, J. S. (2004). Survey of multi-objective optimization methods for engineering. Structural and Multidisciplinary Optimization, 26(6), 369–395.

    Article  MATH  MathSciNet  Google Scholar 

  19. Miettinen, K. (1999). Nonlinear multiobjective optimization. Boston: Kluwer Academic Publishers.

    MATH  Google Scholar 

  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.

    Article  Google Scholar 

  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.

  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 

Download references

Author information

Authors and Affiliations

  1. International Institute of Information Technology, Hyderabad, 500 032, India

    Deepti Singhal & Rama Murthy Garimella

Authors
  1. Deepti Singhal
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Rama Murthy Garimella
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Deepti Singhal.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Singhal, D., Garimella, R.M. Cognitive cross-layer multipath probabilistic routing for cognitive networks. Wireless Netw 21, 1181–1192 (2015). https://doi.org/10.1007/s11276-014-0847-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-014-0847-2

Keywords