DOI QR코드

DOI QR Code

FTCARP: A Fault-Tolerant Routing Protocol for Cognitive Radio Ad Hoc Networks

  • Che-aron, Zamree (Department of Electrical and Computer Engineering, International Islamic University Malaysia) ;
  • Abdalla, Aisha Hassan (Department of Electrical and Computer Engineering, International Islamic University Malaysia) ;
  • Abdullah, Khaizuran (Department of Electrical and Computer Engineering, International Islamic University Malaysia) ;
  • Rahman, Md. Arafatur (Department of Biomedical Electronics and Telecommunications Engineering, University of Naples Federico II)
  • Received : 2013.07.15
  • Accepted : 2014.01.15
  • Published : 2014.02.27

Abstract

Cognitive Radio (CR) has been recently proposed as a promising technology to remedy the problems of spectrum scarcity and spectrum underutilization by enabling unlicensed users to opportunistically utilize temporally unused licensed spectrums in a cautious manner. In Cognitive Radio Ad Hoc Networks (CRAHNs), data routing is one of the most challenging tasks since the channel availability and node mobility are unpredictable. Moreover, the network performance is severely degraded due to large numbers of path failures. In this paper, we propose the Fault-Tolerant Cognitive Ad-hoc Routing Protocol (FTCARP) to provide fast and efficient route recovery in presence of path failures during data delivery in CRAHNs. The protocol exploits the joint path and spectrum diversity to offer reliable communication and efficient spectrum usage over the networks. In the proposed protocol, a backup path is utilized in case a failure occurs over a primary transmission route. Different cause of a path failure will be handled by different route recovery mechanism. The protocol performance is compared with that of the Dual Diversity Cognitive Ad-hoc Routing Protocol (D2CARP). The simulation results obviously prove that FTCARP outperforms D2CARP in terms of throughput, packet loss, end-to-end delay and jitter in the high path-failure rate CRAHNs.

Keywords

References

  1. M.McHenry, "Spectrum white space measurements," in Presentation to New America Foundation Broadband Forum, June 20, 2003.
  2. S. Haykin, "Cognitive radio: brain-empowered wireless communications," IEEE Journal on Selected Areas in Communications, vol. 23, no. 2, pp. 201-220, February, 2005. https://doi.org/10.1109/JSAC.2004.839380
  3. I. F. Akyildiz, W.-Y. Lee, M. C. Vuran and S. Mohanty, "Next generation /dynamic spectrum access/cognitive radio wireless networks: a survey," Computer Networks, vol. 50, no. 1, pp. 2127-2159, May, 2006. https://doi.org/10.1016/j.comnet.2006.05.001
  4. I. F. Akyildiz, W.-Y. Lee and K. R. Chowdhury, "CRAHNs: cognitive radio ad hoc networks," Ad Hoc Networks, vol. 7, no. 5, pp. 810-836, July, 2009. https://doi.org/10.1016/j.adhoc.2009.01.001
  5. S. Sengupta and K. P. Subbalakshmi, "Open research issues in multi-hop cognitive radio networks," IEEE Communications Magazine, vol. 51, no. 4, pp. 168 - 176, April, 2013.
  6. M. Cesana, F. Cuomo and E. Ekici, "Routing in cognitive radio networks: challenges and solutions," Ad Hoc Networks, vol. 9, no. 3, pp. 228-248, May, 2011. https://doi.org/10.1016/j.adhoc.2010.06.009
  7. C. E. Perkins, E. M. Belding-Royer and S. R. Das, "Ad hoc on-demand distance vector (AODV) routing," RFC 3561, Internet Engineering Task Force (IETF), July, 2003.
  8. D. B. Johnson, Y.-C. Hu and D. A. Maltz, "The dynamic source routing protocol (DSR) for mobile ad hoc networks for IPv4," RCF 4728, Internet Engineering Task Force (IETF), February, 2007.
  9. C. E. Perkins and P. Bhagwat, "Highly dynamic destination-sequenced distance-vector routing (DSDV) for mobile computers," ACM SIGCOMM Computer Communication Review, vol. 24, no. 4, pp. 234-244, October, 1994. https://doi.org/10.1145/190809.190336
  10. T. H. Clausen and P. Jacquet, "Optimized link state routing protocol (OLSR)," RFC 3626, Internet Engineering Task Force (IETF), October, 2003.
  11. G.-M. Zhu, I. F. Akyildiz and G.-S. Kuo, "STOD-RP: a spectrum-tree based on-demand routing protocol for multi-hop cognitive radio networks," in Proc. of IEEE Global Telecommunications Conf. (GLOBECOM), pp. 1-5, Nov. 30 - Dec. 4, 2008.
  12. K. R. Chowdhury and M. D. Felice, "SEARCH: a routing protocol for mobile cognitive radioad-hoc networks," Computer Communications, vol. 32, no. 18, pp. 1983-1997, December, 2009. https://doi.org/10.1016/j.comcom.2009.06.011
  13. A. C. Talay and D. T. Altilar, "UNITED nodes: cluster-based routing protocol for mobile cognitive radio networks," IET Communications, vol. 5, no. 15, pp. 2097-2105, October, 2011. https://doi.org/10.1049/iet-com.2010.0285
  14. A. S. Cacciapuoti, C. Calcagno, M. Caleffi and L. Paura, "CAODV: routing in mobile ad-hoc cognitive radio networks," in Proc. of 3rd IFIP Wireless Days Conf. (WD), pp. 1-5, October 20-22, 2010.
  15. M. A. Rahman, M. Caleffi and L. Paura, "Joint path and spectrum diversity in cognitive radio ad-hoc networks," EURASIP Journal on Wireless Communications and Networking, vol. 2012, no. 1, pp. 1-9, July, 2012. https://doi.org/10.1186/1687-1499-2012-1
  16. The VINT Project, "The network simulator - ns-2," 1995.
  17. F. Rocha, "NS2 visual trace analyzer," 2012.